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Real-world example for non-spatial geoprocessing #119

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enauj opened this issue Oct 2, 2024 · 3 comments
Open

Real-world example for non-spatial geoprocessing #119

enauj opened this issue Oct 2, 2024 · 3 comments
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content Changes on content of text. e.g. if something is technical, not correct. enhancement Add new feature like text/ picture/video module 5

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@enauj
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enauj commented Oct 2, 2024

In Module 5: Non-Spatial Geoprocessing it would be really nice to have one or two examples about calculating a new field in the attribute table (using the field calculator) and representing the new field on a map.
Could also be merging two datasets non-spatially or calculating an indicator.

@enauj enauj added content Changes on content of text. e.g. if something is technical, not correct. enhancement Add new feature like text/ picture/video module 5 labels Oct 2, 2024
@ioalexei
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ioalexei commented Oct 3, 2024

For merging two datasets, an obvious one would be merging population data with admin boundaries based on p-codes (both from OCHA Common Operational Datasets published on HDX) - this is very common.

Another very common task is using field calculator to cast data type where it's been encoded or imported incorrectly, e.g. from string to int. This one isn't specific to humanitarian uses/data but is something people will come across a lot using messy data.

@ioalexei
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ioalexei commented Oct 3, 2024

Another example that could combine field calculator and attribute join:
if you have data only with e.g. admin3 pcode but boundaries only at admin2, you can calculate a field to take just the admin2 part of the admin3 pcode and join that to an admin 2 layer...

e.g. if admin 3 pcode is 010204, you can derive admin 2 pcode with formula left($admin3, 4)

@isikl
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isikl commented Oct 4, 2024

For merging two datasets, an obvious one would be merging population data with admin boundaries based on p-codes (both from OCHA Common Operational Datasets published on HDX) - this is very common.

Yes I agree! This is often very much needed. Another similiar example: Joining admin boundaries with data on Multi Poverty Index (available in Excel file) containing pcodes. This exercise could be reused: https://giscience.github.io/gis-training-resource-center/content/Modul_5/en_qgis_modul_5_ex3.html#task-3-mpi-data but there might be definetly more adequate examples. reach out to me or Alec if you have question to this exercise.

Another very common task is using field calculator to cast data type where it's been encoded or imported incorrectly, e.g. from string to int. This one isn't specific to humanitarian uses/data but is something people will come across a lot using messy data.

In the newer QGIS versions there is now a tool called "Refactor Fields", which might replace this task in the future. However, practicing this step is always good and an easy example.

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